Geological engineering parameters influencing CO2-enhanced coalbed methane recovery and sequestration capacity

CO2-enhanced coalbed methane recovery (CO2-ECBM) offers the dual benefit of improving methane production while simultaneously enabling CO2 sequestration, thereby supporting carbon-neutral energy development. However, the coupled effects of geological and engineering parameters on recovery and storage performance in deep, low-permeability coal reservoirs remain insufficiently understood. In this study, a fully coupled thermo–hydro–mechanical model was developed to describe CO2–CH4 competitive adsorption, diffusion-seepage, dissolution, and dynamic permeability evolution in coal reservoirs. After validation against field production data from the South Yanchuan block and published simulation results, the model was applied to evaluate the influences of injection pressure and initial permeability on CO2-ECBM performance under representative geological and engineering conditions. Compared with primary depletion, the simulated CO2-ECBM process increases the stable CH4 production rate by ∼31.8% and the cumulative CH4 production by about 39.5%. Under the investigated conditions, the cumulative CO2 sequestration amount reaches 41 273 m3 at an injection pressure of 12 MPa. The simulation results indicate that increasing injection pressure and initial permeability can enhance both CH4 recovery and CO2 storage, but the response is nonlinear. Specifically, higher injection pressure strengthens pressure-driven transport and competitive adsorption, whereas adsorption-induced swelling and stress-related fracture closure near the injection well progressively offset the incremental benefit to methane recovery. In addition, higher initial permeability improves fracture connectivity, pressure propagation, and matrix-fracture mass transfer efficiency, thereby promoting both gas displacement and sequestration performance. Overall, this study provides mechanistic insight and scenario-based guidance for evaluating CO2-ECBM feasibility, parameter matching, and engineering optimization in deep, low-permeability coal reservoirs.